Construction of a High-Density Genetic Map Based on SLAF Markers and QTL Analysis of Leaf Size in Rice

Identification and Functional Analysis of Candidate Genes Influencing Citrus Leaf Size Through Transcriptome and Coexpression Network Approaches

BACKGROUND

Leaves are the main organs involved in photosynthesis. They capture light energy and promote gas exchange, and their size and shape affect yield. Identifying the regulatory networks and key genes that control citrus leaf size is essential for increasing citrus crop yield.

METHODS

In this study, transcriptome sequencing was performed on three leaf materials: the 'Cuimi' kumquat (Nor) variety and its leaf variants, larger-leaf (VarB) and smaller-leaf (VarS) varieties.

RESULTS

Correlation and principal component analyses revealed a relatively close correlation between Nor and VarS. A total of 7264 differentially expressed genes (DEGs), including 2374 transcription factors (TFs), were identified, and 254 DEGs were common among the three materials. GO and KEGG enrichment analyses revealed significant enrichment in glucose metabolism, cell wall composition, starch biosynthesis, and photosynthesis pathways. WGCNA identified three specific modules related to the different leaf sizes of these three citrus materials. Fifteen candidate genes related to leaf size, including three transcription factors, Fh5g30470 (MYB), Fh7g07360 (AP2/ERF), and Fh5g02470 (SAP), were identified on the basis of connectivity and functional annotations.

CONCLUSIONS

These findings provide a theoretical foundation for a deeper understanding of the molecular mechanisms underlying citrus leaf size and offer new genetic resources for the study of citrus leaf size.

Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations

Zinc (Zn) biofortification of rice can address Zn malnutrition in Asia. Identification and introgression of QTLs for grain Zn content and yield (YLD) can improve the efficiency of rice Zn biofortification. In four rice populations we detected 56 QTLs for seven traits by inclusive composite interval mapping (ICIM), and 16 QTLs for two traits (YLD and Zn) by association mapping. The phenotypic variance (PV) varied from 4.5% (qPN 4.1 ) to 31.7% (qPH 1.1 ). qDF 1.1 , qDF 7.2 , qDF 8.1 , qPH 1.1 , qPH 7.1 , qPL 1.2 , qPL 9.1, qZn 5.1 , qZn 5.2 , qZn 6.1 and qZn 7.1 were identified in both dry and wet seasons; qZn 5.1 , qZn 5.2 , qZn 5.3, qZn 6.2, qZn 7.1 and qYLD 1.2 were detected by both ICIM and association mapping. qZn 7.1 had the highest PV (17.8%) and additive effect (2.5 ppm). Epistasis and QTL co-locations were also observed for different traits. The multi-trait genomic prediction values were 0.24 and 0.16 for YLD and Zn respectively. qZn 6.2 was co-located with a gene (OsHMA2) involved in Zn transport. These results are useful for Zn biofortificatiton of rice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13562-024-00886-0.

Quantitative trait locus mapping for important yield traits of a sorghum-sudangrass hybrid using a high-density single nucleotide polymorphism map

The sorghum-sudangrass hybrid is a vital gramineous herbage.The F2 population was obtained to clarify genetic regularities among the traits of sorghum-sudangrass hybrids by bagging and selfing in the F1 generation using 'scattered ear sorghum' and 'red hull sudangrass.' This hybrid combines the characteristics of the strong resistance of parents, high yield, and good palatability and has clear heterosis. A thorough understanding of the genetic mechanisms of yield traits in sorghum-sudangrass hybrids is essential in improving their yield. Therefore, we conducted quantitative trait locus (QTL) mapping for plant height, stem diameter, tiller number, leaf number, leaf length, leaf width, and fresh weight of each plant in three different environments, using a high-density genetic linkage map based on single nucleotide polymorphism markers previously constructed by our team. A total of 55 QTLs were detected, uniformly distributed over the 10 linkage groups (LGs), with logarithm of odds values ranging between 2.5 and 7.1, which could explain the 4.9-52.44% phenotypic variation. Furthermore, 17 yield-related relatively high-frequency QTL (RHF-QTL) loci were repeatedly detected in at least two environments, with an explanatory phenotypic variation of 4.9-30.97%. No RHF-QTLs were associated with the tiller number. The genes within the confidence interval of RHF-QTL were annotated, and seven candidate genes related to yield traits were screened. Three QTL sites overlapping or adjacent to previous studies were detected by comparative analysis. We also found that QTL was enriched and that qLL-10-1 and qFW-10-4 were located at the same location of 25.81 cM on LG10. The results of this study provide a foundation for QTL fine mapping, candidate gene cloning, and molecular marker-assisted breeding of sorghum-sudangrass hybrids.

Construction of a High-Density Recombination Bin-Based Genetic Map Facilitates High-Resolution Mapping of a Major QTL Underlying Anthocyanin Pigmentation in Eggplant

High-density genetic maps can significantly improve the resolution of QTL mapping. We constructed a high-density recombination bin-based genetic map of eggplant based on 200 F₂ plants from an interspecific cross (Solanum melongena × S. incanum) using the whole genome resequencing strategy. The map was 2022.8 cM long, covering near 99% of the eggplant genome. The map contained 3776 bins, with 3644 (96.5%) being effective (position non-redundant) ones, giving a nominal average distance of 0.54 cM and an effective average distance of 0.56 cM between adjacent bins, respectively. Using this map and 172 F_2:3 lines, a major QTL with pleiotropic effects on two anthocyanin pigmentation-related traits, leaf vein color (LVC) and fruit pericarp color (FPC), was steadily detected in a bin interval of 2.28 cM (or 1.68 Mb) on chromosome E10 in two cropping seasons, explaining ~65% and 55% of the phenotypic variation in LVC and FPC, respectively. Genome-wide association analysis in this population validated the QTL and demonstrated the correctness of mapping two bins of chromosome E02 onto E10. Bioinformatics analysis suggested that a WDR protein gene inside the bin interval with reliable effective variation between the two parents could be a possible candidate gene of the QTL.

Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency

Leaf width was correlated with plant-level transpiration efficiency and associated with 19 QTL in sorghum, suggesting it could be a surrogate for transpiration efficiency in large breeding program. Enhancing plant transpiration efficiency (TE) by reducing transpiration without compromising photosynthesis and yield is a desirable selection target in crop improvement programs. While narrow individual leaf width has been correlated with greater intrinsic water use efficiency in C₄ species, the extent to which this translates to greater plant TE has not been investigated. The aims of this study were to evaluate the correlation of leaf width with TE at the whole-plant scale and investigate the genetic control of leaf width in sorghum. Two lysimetry experiments using 16 genotypes varying for stomatal conductance and three field trials using a large sorghum diversity panel (n = 701 lines) were conducted. Negative associations of leaf width with plant TE were found in the lysimetry experiments, suggesting narrow leaves may result in reduced plant transpiration without trade-offs in biomass accumulation. A wide range in width of the largest leaf was found in the sorghum diversity panel with consistent ranking among sorghum races, suggesting that environmental adaptation may have a role in modifying leaf width. Nineteen QTL were identified by genome-wide association studies on leaf width adjusted for flowering time. The QTL identified showed high levels of correspondence with those in maize and rice, suggesting similarities in the genetic control of leaf width across cereals. Three a priori candidate genes for leaf width, previously found to regulate dorsoventrality, were identified based on a 1-cM threshold. This study provides useful physiological and genetic insights for potential manipulation of leaf width to improve plant adaptation to diverse environments.

Development and Characterization of Chromosome Segment Substitution Lines Derived from Oryza rufipogon in the Background of the Oryza sativa indica Restorer Line R974

Dongxiang wild rice (DXWR) (O. rufipogon Griff.), which has the northernmost worldwide distribution of a wild rice species, is a valuable genetic resource with respect to improving stress tolerance in cultivated rice (Oryza sativa L.). In the three-line hybrid rice breeding system, restorer lines play important roles in enhancing the tolerance of hybrid rice. However, restorer lines have yet to be used as a genomic background for development of substitution lines carrying DXWR chromosome segments. We developed a set of 84 chromosome segment substitution lines (CSSLs) from a donor parent DXWR × recurrent parent restorer line R974 (Oryza sativa indica) cross. On average, each CSSL carried 6.27 introgressed homozygous segments, with 93.37% total genome coverage. Using these CSSLs, we identified a single QTL, qDYST-1, associated with salt stress tolerance on chromosome 3. Furthermore, five CSSLs showing strong salt stress tolerance were subjected to whole-genome single-nucleotide polymorphism chip analyses, during which we detected a common substitution segment containing qDYST-1 in all five CSSLs, thereby implying the validity and efficacy of qDYST-1. These novel CSSLs could make a significant contribution to detecting valuable DXWR QTLs, and provide important germplasm resources for breeding novel restorer lines for use in hybrid rice breeding systems.

TaKLU Plays as a Time Regulator of Leaf Growth via Auxin Signaling

The growth of leaves is subject to strict time regulation. Several genes influencing leaf growth have been identified, but little is known about how genes regulate the orderly initiation and growth of leaves. Here, we demonstrate that TaKLU/TaCYP78A5 contributes to a time regulation mechanism in leaves from initiation to expansion. TaKLU encodes the cytochrome P450 CYP78A5, and its homolog AtKLU has been described whose deletion is detrimental to organ growth. Our results show that TaKLU overexpression increases leaf size and biomass by altering the time of leaf initiation and expansion. TaKLU-overexpressing plants have larger leaves with more cells. Further dynamic observations indicate that enlarged wheat leaves have experienced a longer expansion time. Different from AtKLU inactivation increases leaf number and initiation rates, TaKLU overexpression only smooths the fluctuations of leaf initiation rates by adjusting the initiation time of local leaves, without affecting the overall leaf number and initiation rates. In addition, complementary analyses suggest TaKLU is functionally conserved with AtKLU in controlling the leaf initiation and size and may involve auxin accumulation. Our results provide a new insight into the time regulation mechanisms of leaf growth in wheat.

A High-Density Genetic Linkage Map and Fine Mapping of QTL For Feed Conversion Efficiency in Common Carp (Cyprinus carpio)

Feed conversion efficiency (FCE) is an economically crucial trait in fish, however, little progress has been made in genetics and genomics for this trait because phenotypes of the trait are difficult to measure. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,416 SNP markers for common carp (Cyprinus carpio) based on high throughput genotyping with the carp 250K single nucleotide polymorphism (SNP) array in a full-sib F1 family of mirror carp (Cyprinus carpio) consisting of 141 progenies. The linkage map contained 11,983 distinct loci and spanned 3,590.09 cM with an average locus interval of 0.33 cM. A total of 17 QTL for the FCE trait were detected on four LGs (LG9, LG20, LG28, and LG32), explaining 8.9-15.9% of the phenotypic variations. One major cluster containing eight QTL (qFCE1-28, qFCE2-28, qFCE3-28, qFCE4-28, qFCE5-28, qFCE6-28, qFCE7-28, and qFCE8-28) was detected on LG28. Two clusters consisting of four QTL (qFCE1-32, qFCE2-32, qFCE3-32, and qFCE4-32) and three QTL (qFCE1-20, qFCE2-20, and qFCE3-20) were detected on LG32 and LG20, respectively. Nine candidate genes (ACACA, SCAF4, SLC2A5, TNMD, PCDH1, FOXO, AGO1, FFAR3, and ARID1A) underlying the feed efficiency trait were also identified, the biological functions of which may be involved in lipid metabolism, carbohydrate metabolism, energy deposition, fat accumulation, digestion, growth regulation, and cell proliferation and differentiation according to GO (Gene Ontology). As an important tool, high-density and high-resolution genetic linkage maps play a crucial role in the QTL fine mapping of economically important traits. Our novel findings provided new insights that elucidate the genetic basis and molecular mechanism of feed efficiency and the subsequent marker-assisted selection breeding in common carp.

Improved Genetic Map Identified Major QTLs for Drought Tolerance- and Iron Deficiency Tolerance-Related Traits in Groundnut

A deep understanding of the genetic control of drought tolerance and iron deficiency tolerance is essential to hasten the process of developing improved varieties with higher tolerance through genomics-assisted breeding. In this context, an improved genetic map with 1205 loci was developed spanning 2598.3 cM with an average 2.2 cM distance between loci in the recombinant inbred line (TAG 24 × ICGV 86031) population using high-density 58K single nucleotide polymorphism (SNP) “Axiom_Arachis” array. Quantitative trait locus (QTL) analysis was performed using extensive phenotyping data generated for 20 drought tolerance- and two iron deficiency tolerance-related traits from eight seasons (2004–2015) at two locations in India, one in Niger, and one in Senegal. The genome-wide QTL discovery analysis identified 19 major main-effect QTLs with 10.0–33.9% phenotypic variation explained (PVE) for drought tolerance- and iron deficiency tolerance- related traits. Major main-effect QTLs were detected for haulm weight (20.1% PVE), SCMR (soil plant analytical development (SPAD) chlorophyll meter reading, 22.4% PVE), and visual chlorosis rate (33.9% PVE). Several important candidate genes encoding glycosyl hydrolases; malate dehydrogenases; microtubule-associated proteins; and transcription factors such as MADS-box, basic helix-loop-helix (bHLH), NAM, ATAF, and CUC (NAC), and myeloblastosis (MYB) were identified underlying these QTL regions. The putative function of these genes indicated their possible involvement in plant growth, development of seed and pod, and photosynthesis under drought or iron deficiency conditions in groundnut. These genomic regions and candidate genes, after validation, may be useful to develop molecular markers for deploying genomics-assisted breeding for enhancing groundnut yield under drought stress and iron-deficient soil conditions.

A High-Density Genetic Linkage Map of SLAFs and QTL Analysis of Grain Size and Weight in Barley (Hordeum vulgare L.)

Grain size is an important agronomic trait determines yield in barley, and a high-density genetic map is helpful to accurately detect quantitative trait loci (QTLs) related to grain traits. Using specific-locus amplified fragment sequencing (SLAF-seq) technology, a high-density genetic map was constructed with a population of 134 recombinant inbred lines (RILs) deriving from a cross between Golden Promise (GP) and H602, which contained 12,635 SLAFs with 26,693 SNPs, and spanned 896.74 cM with an average interval of 0.07 cM on seven chromosomes. Based on the map, a total of 16 QTLs for grain length (GL), grain width and thousand-grain weight were detected on 1H, 2H, 4H, 5H, and 6H. Among them, a major QTL locus qGL1, accounting for the max phenotypic variance of 16.7% was located on 1H, which is a new unreported QTL affecting GL. In addition, the other two QTLs, qGL5 and qTGW5, accounting for the max phenotypic variances of 20.7 and 21.1%, respectively, were identified in the same region, and sequencing results showed they are identical to HvDep1 gene. These results indicate that it is a feasible approach to construct a high-quality genetic map for QTL mapping by using SLAF markers, and the detected major QTLs qGL1, qGL5, and qTGW5 are useful for marker-assisted selection (MAS) of grain size in barley breeding.